Elected to Upsilon Pi Epsilon, the international honor society for the computing and information disciplines, recognizing academic achievement and contributions in computer science.
About
I'm an AI researcher and engineer working across the full stack of technical systems, from embedded hardware and space systems to the internals of modern machine learning models.
I focus on building systems that are both rigorous and real, combining production-grade engineering with experiments that produce genuine insight rather than just impressive metrics.
I currently work as an AI Research Assistant developing machine learning systems for speech and biosignal understanding. Previously, I worked as a Software Engineering Intern (Machine Learning Focus) at Capital Technology Group, contributing to ML systems operating on large government and financial datasets for anomaly detection, trade surveillance, and predictive analytics.
Outside of research, I build systems that connect theory with deployment, including embedded platforms, data infrastructure, and technical software.
Some of the systems I'm currently building can't be public yet. When they are, they'll probably show up here.
Updates
NOWCurrent work
Current Focus
Continuing my work as an AI Research Assistant while pursuing additional research and technical initiatives across machine learning, embedded systems, and data-driven infrastructure.
- Speech & alignment research
- Ongoing technical research
- Private ventures in progress
Presented architecture design, training setup, and early evaluation results for state-space model based speech enhancement research focused on difficult sensing environments and biosignal-derived audio. Because of publication rules, I cannot publicly share full details until the work is submitted to a conference. This section will be updated once submission is complete.
Continued development work on embedded systems and mission-level engineering for the Wentworth PocketQube satellite program, contributing to spacecraft subsystem development and flight-adjacent systems engineering.
Began working as an AI Research Assistant contributing to machine learning research focused on speech and biosignal understanding. Work involves designing model architectures, developing training pipelines, and evaluating machine learning systems for challenging sensing environments.
Designed and deployed machine learning systems and data pipelines analyzing large government and financial datasets. Work included anomaly detection models, predictive analytics, and infrastructure supporting complex regulatory environments.
Initiated research investigating mechanisms and mitigation strategies for sycophantic behavior in modern language models. The project focuses on interpretability, evaluation benchmarks, and alignment techniques. Because of publication rules, I cannot publicly share full technical details until the work is submitted to a conference. This section will be updated after submission.
Started exploratory research investigating the engineering feasibility of large-scale tether-based space infrastructure and next-generation orbital systems. Because of publication rules and ongoing research development, technical details cannot yet be publicly shared. This section will be updated when the work progresses further.
Initiated development of a private technical system focused on financial infrastructure and data systems. The project remains in private development.
Began contributing to embedded systems engineering for the Wentworth PocketQube satellite mission, working on spacecraft subsystems and mission-level technical design.
Awarded the Massachusetts Police Association scholarship recognizing academic achievement and leadership.
Worked on technical infrastructure, hardware support, and systems operations across campus computing environments.
Provided tutoring support in computer science and mathematics, helping students build programming fundamentals and quantitative problem-solving skills.
Several software and infrastructure systems currently under development that will be released publicly when ready.
Began undergraduate studies in Computer Science with minors in Applied Mathematics and Data Science at Wentworth Institute of Technology.
Launched Strive Technology Group, an early-stage technical venture focused on building software systems and technical infrastructure. Initial work included software development, engineering experimentation, and early technical product development.
Experience
- Machine Learning
- PyTorch
- Deep Learning
- Model Training
- Research Engineering
- Machine Learning
- Python
- Data Engineering
- Predictive Modeling
- Data Pipelines
- Teaching
- Computer Science
- Algorithms
- Mathematics
- Technical Communication
- IT Systems
- Technical Support
- System Administration
- Hardware Troubleshooting
- Entrepreneurship
- Software Architecture
- Full-Stack Development
- System Design
- Product Development